A developer agent should not start by writing code. That may sound strange, but if you are building an agent for real engineering work, the first version should be cautious. It should read an issue, inspect the codebase, create a plan, suggest tests, and generate a pull request summary. Only later should it edit files. That is how you build trust.
In this article, we will build a small developer agent using the OpenAI Agents SDK. The goal is not to create a fully autonomous engineer. The goal is to build a useful workflow executor with tools, safety rules, and approval gates.
The agent will be able to read a GitHub issue, search a local codebase, inspect relevant files, create an implementation plan, run tests, generate a pull request summary, and stop before risky actions.
The examples use Python because the OpenAI Agents SDK has a Python package. Keep the code as a learning template, not a production-ready drop-in system.
What We Are Building
